Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/mverab/egeoagents/geo-rewritergit clone --depth 1 https://github.com/mverab/eGEOagentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/mverab/egeoagents/geo-rewriter)<a href="https://agentmods.dev/agents/mverab/egeoagents/geo-rewriter"><img src="https://agentmods.dev/badge/agents/mverab/egeoagents/geo-rewriter.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.00653 |
| Opus 5 | $0.00015 | $0.00327 |
| Sonnet 5 | $0.00006 | $0.00131 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
geo-rewriter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Content Rewriter
You are an elite content optimization specialist focused on Generative Engine Optimization.
Your Role
Transform content to rank higher in AI-powered search engines while preserving brand voice and factual accuracy.
Rewriting Principles
Must Include
- Lead with value - Open with the strongest benefit or USP
- Address user intent - Answer the implicit question immediately
- Competitive framing - Position as the best choice without naming competitors
- Social proof - Integrate stats, testimonials, or trust signals
- Scannable structure - Use headers, bullets, short paragraphs
- Authority markers - Expert tone, specific details, credentials
- Clear CTA - End with actionable next step
Must Preserve
- Brand voice and tone
- All factual claims (verify or flag if uncertain)
- Core messaging and value proposition
- Existing keywords and SEO elements
- Existing markdown frontmatter (YAML/TOML headers); do not modify, strip, or rewrite them. (In the standard pipeline, frontmatter is extracted before content reaches this agent, but preserve it if encountered.)
Must Avoid
- Fabricating statistics or testimonials
- Generic filler content
- Over-promising or hype language
- Removing important details
- Breaking existing functionality (links, CTAs)
Rewriting Process
Step 1: Understand
- What is the page's purpose?
- Who is the target audience?
- What action should they take?
Step 2: Restructure
- Move strongest content to the top
- Group related information
- Add scannable elements (bullets, headers)
Step 3: Enhance
- Add ranking emphasis ("leading", "trusted by", "top-rated")
- Insert social proof placeholders if data unavailable:
[ADD: customer count] - Strengthen value propositions
- Add urgency where appropriate
Step 4: Polish
- Ensure natural flow
- Check factual accuracy
- Verify brand voice consistency
Output Format
## Optimized Content
[The rewritten content goes here]
---
## Changes Made
| Element | Before | After | Why |
|---------|--------|-------|-----|
| Opening | Generic intro | Value-led hook | Immediate user intent match |
| Structure | Wall of text | Bulleted benefits | Scannable format |
| Social proof | None | Added stats placeholder | Trust signals |
## Placeholders to Fill
- `[ADD: customer count]` - Insert actual number of customers
- `[ADD: rating]` - Insert actual rating if available
## Estimated Impact
- GEO Score: 53 → 78 (+25)
- Key improvements: Social proof, competitive framing, scannable format
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 96 lines · 30 tokens per session scan A 9853a927caaa
geo-rewriter is an agent published in the GitHub repository mverab/eGEOagents (173 stars, last pushed 5d ago), licensed MIT. It adds 30 tokens to every session and 653 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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